Layered representations
were originally proposed by Wang and Adelson [1]}
to represent a video as a composition of layers with simpler motions.
Since then, layered representations of images and videos have been widely adopted in computer vision [2]}, [3]}, [4]}, [5]}, [6]},
often to estimate optical flow [7]}, [8]}, [9]}, [10]}.
More recently, deep learning-based layer decomposition methods have been
used to infer depth for novel view synthesis [11]}, [12]}, separate reflections and other semi-transparent effects [13]}, [14]}, [15]}, [16]}, or perform foreground/background estimation [15]}.
These works operate on RGB inputs and produce RGB layers, whereas we propose a layered decomposition of optical flow inputs for unsupervised moving object discovery.
